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2020 – today
- 2023
[j11]Chenxu Zhu
, Bo Chen, Weinan Zhang, Jincai Lai, Ruiming Tang, Xiuqiang He, Zhenguo Li, Yong Yu:
AIM: Automatic Interaction Machine for Click-Through Rate Prediction. IEEE Trans. Knowl. Data Eng. 35(4): 3389-3403 (2023)- [j10]Haokun Chen, Chenxu Zhu, Ruiming Tang, Weinan Zhang, Xiuqiang He, Yong Yu:
Large-Scale Interactive Recommendation With Tree-Structured Reinforcement Learning. IEEE Trans. Knowl. Data Eng. 35(4): 4018-4032 (2023) - [c93]Jing Wang, Mengchen Zhao, Wei Xia, Zhenhua Dong, Ruiming Tang, Rui Zhang, Jianye Hao, Guangyong Chen, Pheng-Ann Heng:
RLMixer: A Reinforcement Learning Approach for Integrated Ranking with Contrastive User Preference Modeling. PAKDD (3) 2023: 400-413 - [c92]Chenxu Zhu, Bo Chen, Huifeng Guo, Hang Xu, Xiangyang Li, Xiangyu Zhao, Weinan Zhang, Yong Yu, Ruiming Tang:
AutoGen: An Automated Dynamic Model Generation Framework for Recommender System. WSDM 2023: 598-606 - [c91]Lingyue Fu, Jianghao Lin, Weiwen Liu, Ruiming Tang, Weinan Zhang, Rui Zhang, Yong Yu:
An F-shape Click Model for Information Retrieval on Multi-block Mobile Pages. WSDM 2023: 1057-1065 - [c90]Yunjia Xi, Jianghao Lin, Weiwen Liu, Xinyi Dai, Weinan Zhang, Rui Zhang, Ruiming Tang, Yong Yu:
A Bird's-eye View of Reranking: From List Level to Page Level. WSDM 2023: 1075-1083 - [c89]Ruiming Tang, Bo Chen, Yejing Wang, Huifeng Guo, Yong Liu, Wenqi Fan, Xiangyu Zhao:
AutoML for Deep Recommender Systems: Fundamentals and Advances. WSDM 2023: 1264-1267 - [c88]Menghui Zhu, Wei Xia, Weiwen Liu, Yifan Liu, Ruiming Tang, Weinan Zhang:
Integrated Ranking for News Feed with Reinforcement Learning. WWW (Companion Volume) 2023: 480-484 - [c87]Xiaofan Liu, Qinglin Jia, Chuhan Wu, Jingjie Li, Quanyu Dai, Lin Bo, Rui Zhang, Ruiming Tang:
Task Adaptive Multi-learner Network for Joint CTR and CVR Estimation. WWW (Companion Volume) 2023: 490-494 - [c86]Wei Guo, Chang Meng, Enming Yuan, Zhicheng He, Huifeng Guo, Yingxue Zhang, Bo Chen, Yaochen Hu, Ruiming Tang, Xiu Li, Rui Zhang:
Compressed Interaction Graph based Framework for Multi-behavior Recommendation. WWW 2023: 960-970 - [c85]Bowei He, Xu He, Yingxue Zhang, Ruiming Tang, Chen Ma:
Dynamically Expandable Graph Convolution for Streaming Recommendation. WWW 2023: 1457-1467 - [i63]Yuhao Wang, Ha Tsz Lam, Yi Wong, Ziru Liu, Xiangyu Zhao, Yichao Wang, Bo Chen, Huifeng Guo, Ruiming Tang:
Multi-Task Deep Recommender Systems: A Survey. CoRR abs/2302.03525 (2023) - [i62]Zhicheng He, Weiwen Liu, Wei Guo, Jiarui Qin, Yingxue Zhang, Yaochen Hu, Ruiming Tang:
A Survey on User Behavior Modeling in Recommender Systems. CoRR abs/2302.11087 (2023) - [i61]Xu Chen, Jingsen Zhang, Lei Wang, Quanyu Dai, Zhenhua Dong, Ruiming Tang, Rui Zhang, Li Chen, Ji-Rong Wen:
REASONER: An Explainable Recommendation Dataset with Multi-aspect Real User Labeled Ground Truths Towards more Measurable Explainable Recommendation. CoRR abs/2303.00168 (2023) - [i60]Wei Guo, Chang Meng, Enming Yuan, Zhicheng He, Huifeng Guo, Yingxue Zhang, Bo Chen, Yaochen Hu, Ruiming Tang, Xiu Li, Rui Zhang:
Compressed Interaction Graph based Framework for Multi-behavior Recommendation. CoRR abs/2303.02418 (2023) - [i59]Bowei He, Xu He, Yingxue Zhang, Ruiming Tang, Chen Ma:
Dynamically Expandable Graph Convolution for Streaming Recommendation. CoRR abs/2303.11700 (2023) - [i58]Yuening Wang, Yingxue Zhang, Antonios Valkanas, Ruiming Tang, Chen Ma, Jianye Hao, Mark Coates:
Structure Aware Incremental Learning with Personalized Imitation Weights for Recommender Systems. CoRR abs/2305.01204 (2023) - 2022
- [j9]Xiangli Yang, Qing Liu, Rong Su, Ruiming Tang, Zhirong Liu, Xiuqiang He, Jianxi Yang:
Click-through rate prediction using transfer learning with fine-tuned parameters. Inf. Sci. 612: 188-200 (2022) - [j8]Niannan Xue, Bin Liu, Huifeng Guo, Ruiming Tang, Fengwei Zhou, Stefanos Zafeiriou, Yuzhou Zhang, Jun Wang, Zhenguo Li:
AutoHash: Learning Higher-Order Feature Interactions for Deep CTR Prediction. IEEE Trans. Knowl. Data Eng. 34(6): 2653-2666 (2022) - [j7]Xinyi Dai, Yunjia Xi, Weinan Zhang, Qing Liu, Ruiming Tang, Xiuqiang He, Jiawei Hou, Jun Wang, Yong Yu:
Beyond Relevance Ranking: A General Graph Matching Framework for Utility-Oriented Learning to Rank. ACM Trans. Inf. Syst. 40(2): 25:1-25:29 (2022) - [c84]Fuyuan Lyu, Xing Tang, Hong Zhu, Huifeng Guo, Yingxue Zhang, Ruiming Tang, Xue Liu:
OptEmbed: Learning Optimal Embedding Table for Click-through Rate Prediction. CIKM 2022: 1399-1409 - [c83]Haolun Wu, Chen Ma, Yingxue Zhang, Xue Liu, Ruiming Tang, Mark Coates:
Adapting Triplet Importance of Implicit Feedback for Personalized Recommendation. CIKM 2022: 2148-2157 - [c82]Hengyu Zhang, Enming Yuan, Wei Guo, Zhicheng He, Jiarui Qin, Huifeng Guo, Bo Chen, Xiu Li, Ruiming Tang:
Disentangling Past-Future Modeling in Sequential Recommendation via Dual Networks. CIKM 2022: 2549-2558 - [c81]Bo Chen, Huifeng Guo, Weiwen Liu, Yue Ding, Yunzhe Li, Wei Guo, Yichao Wang, Zhicheng He, Ruiming Tang, Rui Zhang:
Numerical Feature Representation with Hybrid N-ary Encoding. CIKM 2022: 2984-2993 - [c80]Xiangyang Li, Bo Chen, Huifeng Guo, Jingjie Li, Chenxu Zhu, Xiang Long, Sujian Li, Yichao Wang, Wei Guo, Longxia Mao, Jinxing Liu, Zhenhua Dong, Ruiming Tang:
IntTower: The Next Generation of Two-Tower Model for Pre-Ranking System. CIKM 2022: 3292-3301 - [c79]Quanyu Dai, Yalei Lv, Jieming Zhu, Junjie Ye, Zhenhua Dong, Rui Zhang, Shu-Tao Xia, Ruiming Tang:
LCD: Adaptive Label Correction for Denoising Music Recommendation. CIKM 2022: 3903-3907 - [c78]Wei Xia, Weiwen Liu, Yifan Liu, Ruiming Tang:
Balancing Utility and Exposure Fairness for Integrated Ranking with Reinforcement Learning. CIKM 2022: 4590-4594 - [c77]Wei Guo, Can Zhang, Zhicheng He, Jiarui Qin, Huifeng Guo, Bo Chen, Ruiming Tang, Xiuqiang He, Rui Zhang:
MISS: Multi-Interest Self-Supervised Learning Framework for Click-Through Rate Prediction. ICDE 2022: 727-740 - [c76]Fuyuan Lyu, Xing Tang, Huifeng Guo, Ruiming Tang, Xiuqiang He, Rui Zhang, Xue Liu:
Memorize, Factorize, or be Naive: Learning Optimal Feature Interaction Methods for CTR Prediction. ICDE 2022: 1450-1462 - [c75]Fengyi Song, Bo Chen, Xiangyu Zhao, Huifeng Guo, Ruiming Tang:
AutoAssign: Automatic Shared Embedding Assignment in Streaming Recommendation. ICDM 2022: 458-467 - [c74]Weiwen Liu, Yunjia Xi, Jiarui Qin, Fei Sun, Bo Chen, Weinan Zhang, Rui Zhang, Ruiming Tang:
Neural Re-ranking in Multi-stage Recommender Systems: A Review. IJCAI 2022: 5512-5520 - [c73]Yankai Chen, Yifei Zhang, Huifeng Guo, Ruiming Tang, Irwin King:
An Effective Post-training Embedding Binarization Approach for Fast Online Top-K Passage Matching. AACL/IJCNLP (2) 2022: 102-108 - [c72]Yankai Chen, Huifeng Guo, Yingxue Zhang, Chen Ma, Ruiming Tang, Jingjie Li, Irwin King:
Learning Binarized Graph Representations with Multi-faceted Quantization Reinforcement for Top-K Recommendation. KDD 2022: 168-178 - [c71]Zhicheng He, Wei Xia, Kai Dong, Huifeng Guo, Ruiming Tang, Dingyin Xia, Rui Zhang:
Unsupervised Learning Style Classification for Learning Path Generation in Online Education Platforms. KDD 2022: 2997-3006 - [c70]Yichao Wang, Huifeng Guo, Bo Chen, Weiwen Liu, Zhirong Liu, Qi Zhang, Zhicheng He, Hongkun Zheng, Weiwei Yao, Muyu Zhang, Zhenhua Dong, Ruiming Tang:
CausalInt: Causal Inspired Intervention for Multi-Scenario Recommendation. KDD 2022: 4090-4099 - [c69]Roberto Corizzo, Junfeng Ge, Colin Bellinger, Xiaoqiang Zhu, Paula Branco, Kuang-chih Lee, Nathalie Japkowicz, Ruiming Tang, Tao Zhuang, Han Zhu, Biye Jiang, Jiaxin Mao, Weinan Zhang:
4th Workshop on Deep Learning Practice and Theory for High-Dimensional Sparse and Imbalanced Data with KDD 2022. KDD 2022: 4860-4861 - [c68]Weiwen Liu, Jiarui Qin, Ruiming Tang, Bo Chen:
Neural Re-ranking for Multi-stage Recommender Systems. RecSys 2022: 698-699 - [c67]Jiarui Qin, Jiachen Zhu, Bo Chen, Zhirong Liu, Weiwen Liu, Ruiming Tang, Rui Zhang, Yong Yu, Weinan Zhang:
RankFlow: Joint Optimization of Multi-Stage Cascade Ranking Systems as Flows. SIGIR 2022: 814-824 - [c66]Yunjia Xi, Weiwen Liu, Jieming Zhu, Xilong Zhao, Xinyi Dai, Ruiming Tang, Weinan Zhang, Rui Zhang, Yong Yu:
Multi-Level Interaction Reranking with User Behavior History. SIGIR 2022: 1336-1346 - [c65]Enming Yuan, Wei Guo, Zhicheng He, Huifeng Guo, Chengkai Liu, Ruiming Tang:
Multi-Behavior Sequential Transformer Recommender. SIGIR 2022: 1642-1652 - [c64]Guohao Cai, Jieming Zhu, Quanyu Dai, Zhenhua Dong, Xiuqiang He, Ruiming Tang, Rui Zhang:
ReLoop: A Self-Correction Continual Learning Loop for Recommender Systems. SIGIR 2022: 2692-2697 - [c63]Ting Long, Jiarui Qin, Jian Shen, Weinan Zhang, Wei Xia, Ruiming Tang, Xiuqiang He, Yong Yu:
Improving Knowledge Tracing with Collaborative Information. WSDM 2022: 599-607 - [c62]Lu Wang, Ruiming Tang, Xiaofeng He, Xiuqiang He:
Hierarchical Imitation Learning via Subgoal Representation Learning for Dynamic Treatment Recommendation. WSDM 2022: 1081-1089 - [c61]Yi Li, Jieming Zhu, Weiwen Liu, Liangcai Su, Guohao Cai, Qi Zhang, Ruiming Tang, Xi Xiao, Xiuqiang He:
PEAR: Personalized Re-ranking with Contextualized Transformer for Recommendation. WWW (Companion Volume) 2022: 62-66 - [c60]Riccardo Tommasini, Senjuti Basu Roy, Xuan Wang, Hongwei Wang, Heng Ji, Jiawei Han, Preslav Nakov, Giovanni Da San Martino, Firoj Alam, Markus Schedl, Elisabeth Lex, Akash Bharadwaj, Graham Cormode, Milan Dojchinovski, Jan Forberg, Johannes Frey, Pieter Bonte, Marco Balduini, Matteo Belcao, Emanuele Della Valle, Junliang Yu, Hongzhi Yin, Tong Chen, Haochen Liu, Yiqi Wang, Wenqi Fan, Xiaorui Liu, Jamell Dacon, Lingjuan Lye, Jiliang Tang, Aristides Gionis, Stefan Neumann, Bruno Ordozgoiti, Simon Razniewski, Hiba Arnaout, Shrestha Ghosh, Fabian M. Suchanek, Lingfei Wu, Yu Chen, Yunyao Li, Bang Liu, Filip Ilievski, Daniel Garijo, Hans Chalupsky, Pedro A. Szekely, Ilias Kanellos, Dimitris Sacharidis, Thanasis Vergoulis, Nurendra Choudhary, Nikhil Rao, Karthik Subbian, Srinivasan H. Sengamedu, Chandan K. Reddy, Friedhelm Victor, Bernhard Haslhofer, George Katsogiannis-Meimarakis, Georgia Koutrika, Shengmin Jin, Danai Koutra, Reza Zafarani, Yulia Tsvetkov, Vidhisha Balachandran, Sachin Kumar, Xiangyu Zhao, Bo Chen, Huifeng Guo, Yejing Wang, Ruiming Tang, Yang Zhang, Wenjie Wang, Peng Wu, Fuli Feng, Xiangnan He:
Accepted Tutorials at The Web Conference 2022. WWW (Companion Volume) 2022: 391-399 - [c59]Qi Wan, Xiangnan He, Xiang Wang, Jiancan Wu, Wei Guo, Ruiming Tang:
Cross Pairwise Ranking for Unbiased Item Recommendation. WWW 2022: 2370-2378 - [i57]Weijun Hong, Guilin Li, Weinan Zhang, Ruiming Tang, Yunhe Wang, Zhenguo Li, Yong Yu:
DropNAS: Grouped Operation Dropout for Differentiable Architecture Search. CoRR abs/2201.11679 (2022) - [i56]Weiwen Liu, Yunjia Xi, Jiarui Qin, Fei Sun, Bo Chen, Weinan Zhang, Rui Zhang, Ruiming Tang:
Neural Re-ranking in Multi-stage Recommender Systems: A Review. CoRR abs/2202.06602 (2022) - [i55]Yi Li, Jieming Zhu, Weiwen Liu, Liangcai Su, Guohao Cai, Qi Zhang, Ruiming Tang, Xi Xiao, Xiuqiang He:
PEAR: Personalized Re-ranking with Contextualized Transformer for Recommendation. CoRR abs/2203.12267 (2022) - [i54]Bo Chen, Xiangyu Zhao, Yejing Wang, Wenqi Fan, Huifeng Guo, Ruiming Tang:
Automated Machine Learning for Deep Recommender Systems: A Survey. CoRR abs/2204.01390 (2022) - [i53]Yunjia Xi, Weiwen Liu, Jieming Zhu, Xilong Zhao, Xinyi Dai, Ruiming Tang, Weinan Zhang, Rui Zhang, Yong Yu:
Multi-Level Interaction Reranking with User Behavior History. CoRR abs/2204.09370 (2022) - [i52]Guohao Cai, Jieming Zhu, Quanyu Dai, Zhenhua Dong, Xiuqiang He, Ruiming Tang, Rui Zhang:
ReLoop: A Self-Correction Continual Learning Loop for Recommender Systems. CoRR abs/2204.11165 (2022) - [i51]Qi Wan, Xiangnan He, Xiang Wang, Jiancan Wu, Wei Guo, Ruiming Tang:
Cross Pairwise Ranking for Unbiased Item Recommendation. CoRR abs/2204.12176 (2022) - [i50]Yankai Chen, Huifeng Guo, Yingxue Zhang, Chen Ma, Ruiming Tang, Jingjie Li, Irwin King:
Learning Binarized Graph Representations with Multi-faceted Quantization Reinforcement for Top-K Recommendation. CoRR abs/2206.02115 (2022) - [i49]Lingyue Fu, Jianghao Lin, Weiwen Liu, Ruiming Tang, Weinan Zhang, Rui Zhang, Yong Yu:
An F-shape Click Model for Information Retrieval on Multi-block Mobile Pages. CoRR abs/2206.08604 (2022) - [i48]Jianghao Lin, Weiwen Liu, Xinyi Dai, Weinan Zhang, Shuai Li, Ruiming Tang, Xiuqiang He, Jianye Hao, Yong Yu:
A Graph-Enhanced Click Model for Web Search. CoRR abs/2206.08621 (2022) - [i47]Haolun Wu, Chen Ma, Yingxue Zhang, Xue Liu, Ruiming Tang, Mark Coates:
Adapting Triplet Importance of Implicit Feedback for Personalized Recommendation. CoRR abs/2208.01709 (2022) - [i46]Chang Meng, Ziqi Zhao, Wei Guo, Yingxue Zhang, Haolun Wu, Chen Gao, Dong Li, Xiu Li, Ruiming Tang:
Coarse-to-Fine Knowledge-Enhanced Multi-Interest Learning Framework for Multi-Behavior Recommendation. CoRR abs/2208.01849 (2022) - [i45]Fuyuan Lyu, Xing Tang, Hong Zhu, Huifeng Guo, Yingxue Zhang, Ruiming Tang, Xue Liu:
OptEmbed: Learning Optimal Embedding Table for Click-through Rate Prediction. CoRR abs/2208.04482 (2022) - [i44]Yuxiang Shi, Yue Ding, Bo Chen, Yuyang Huang, Ruiming Tang, Dong Wang:
Task Aligned Meta-learning based Augmented Graph for Cold-Start Recommendation. CoRR abs/2208.05716 (2022) - [i43]Zhenhua Dong, Zhe Wang, Jun Xu, Ruiming Tang, Jirong Wen:
A Brief History of Recommender Systems. CoRR abs/2209.01860 (2022) - [i42]Xiangyang Li, Bo Chen, Huifeng Guo, Jingjie Li, Chenxu Zhu, Xiang Long, Sujian Li, Yichao Wang, Wei Guo, Longxia Mao, Jinxing Liu, Zhenhua Dong, Ruiming Tang:
IntTower: the Next Generation of Two-Tower Model for Pre-Ranking System. CoRR abs/2210.09890 (2022) - [i41]Hengyu Zhang, Enming Yuan, Wei Guo, Zhicheng He, Jiarui Qin, Huifeng Guo, Bo Chen, Xiu Li, Ruiming Tang:
Disentangling Past-Future Modeling in Sequential Recommendation via Dual Networks. CoRR abs/2210.14577 (2022) - [i40]Haolun Wu, Yingxue Zhang, Chen Ma, Wei Guo, Ruiming Tang, Xue Liu, Mark Coates:
Intent-aware Multi-source Contrastive Alignment for Tag-enhanced Recommendation. CoRR abs/2211.06370 (2022) - [i39]Yunjia Xi, Jianghao Lin, Weiwen Liu, Xinyi Dai, Weinan Zhang, Rui Zhang, Ruiming Tang, Yong Yu:
A Bird's-eye View of Reranking: from List Level to Page Level. CoRR abs/2211.09303 (2022) - [i38]Shiwei Li, Huifeng Guo, Lu Hou, Wei Zhang, Xing Tang, Ruiming Tang, Rui Zhang, Ruixuan Li:
Adaptive Low-Precision Training for Embeddings in Click-Through Rate Prediction. CoRR abs/2212.05735 (2022) - 2021
- [j6]Handong Ma, Jiawei Hou, Chenxu Zhu, Weinan Zhang, Ruiming Tang, Jincai Lai, Jieming Zhu, Xiuqiang He, Yong Yu:
QA4PRF: A Question Answering Based Framework for Pseudo Relevance Feedback. IEEE Access 9: 139303-139314 (2021) - [c58]Yue Ding, Yuxiang Shi, Bo Chen, Chenghua Lin, Hongtao Lu, Jie Li, Ruiming Tang, Dong Wang:
Semi-deterministic and Contrastive Variational Graph Autoencoder for Recommendation. CIKM 2021: 382-391 - [c57]Yunzhe Li, Yue Ding, Bo Chen, Xin Xin, Yule Wang, Yuxiang Shi, Ruiming Tang, Dong Wang:
Extracting Attentive Social Temporal Excitation for Sequential Recommendation. CIKM 2021: 998-1007 - [c56]Bo Chen, Yichao Wang, Zhirong Liu, Ruiming Tang, Wei Guo, Hongkun Zheng, Weiwei Yao, Muyu Zhang, Xiuqiang He:
Enhancing Explicit and Implicit Feature Interactions via Information Sharing for Parallel Deep CTR Models. CIKM 2021: 3757-3766 - [c55]Weinan Zhang, Jiarui Qin, Wei Guo, Ruiming Tang, Xiuqiang He:
Deep Learning for Click-Through Rate Estimation. IJCAI 2021: 4695-4703 - [c54]Wei Guo, Rong Su, Renhao Tan, Huifeng Guo, Yingxue Zhang, Zhirong Liu, Ruiming Tang, Xiuqiang He:
Dual Graph enhanced Embedding Neural Network for CTR Prediction. KDD 2021: 496-504 - [c53]Jiarui Qin, Weinan Zhang, Rong Su, Zhirong Liu, Weiwen Liu, Ruiming Tang, Xiuqiang He, Yong Yu:
Retrieval & Interaction Machine for Tabular Data Prediction. KDD 2021: 1379-1389 - [c52]Huifeng Guo, Bo Chen, Ruiming Tang, Weinan Zhang, Zhenguo Li, Xiuqiang He:
An Embedding Learning Framework for Numerical Features in CTR Prediction. KDD 2021: 2910-2918 - [c51]Xiaoqiang Zhu, Kuang-chih Lee, Guorui Zhou, Biye Jiang, Zhe Wang, Ruiming Tang, Kan Ren, Qingyao Ai, Weinan Zhang:
3rd International Workshop on Deep Learning Practice for High-Dimensional Sparse Data with KDD 2021. KDD 2021: 4187-4188 - [c50]Yunfeng Lin, Guilin Li, Xing Zhang, Weinan Zhang, Bo Chen, Ruiming Tang, Zhenguo Li, Jiashi Feng, Yong Yu:
ModularNAS: Towards Modularized and Reusable Neural Architecture Search. MLSys 2021 - [c49]Hang Lai, Jian Shen, Weinan Zhang, Yimin Huang, Xing Zhang, Ruiming Tang, Yong Yu, Zhenguo Li:
On Effective Scheduling of Model-based Reinforcement Learning. NeurIPS 2021: 3694-3705 - [c48]Weinan Zhang, Zhengyu Yang, Jian Shen, Minghuan Liu, Yimin Huang, Xing Zhang, Ruiming Tang, Zhenguo Li:
Learning to Build High-Fidelity and Robust Environment Models. ECML/PKDD (1) 2021: 104-121 - [c47]Jianghao Lin, Weiwen Liu, Xinyi Dai, Weinan Zhang, Shuai Li, Ruiming Tang, Xiuqiang He, Jianye Hao, Yong Yu:
A Graph-Enhanced Click Model for Web Search. SIGIR 2021: 1259-1268 - [c46]Huifeng Guo, Wei Guo, Yong Gao, Ruiming Tang, Xiuqiang He, Wenzhi Liu:
ScaleFreeCTR: MixCache-based Distributed Training System for CTR Models with Huge Embedding Table. SIGIR 2021: 1269-1278 - [c45]Xinyi Dai, Jianghao Lin, Weinan Zhang, Shuai Li, Weiwen Liu, Ruiming Tang, Xiuqiang He, Jianye Hao, Jun Wang, Yong Yu:
An Adversarial Imitation Click Model for Information Retrieval. WWW 2021: 1809-1820 - [i37]Chen Ma, Liheng Ma, Yingxue Zhang, Ruiming Tang, Xue Liu, Mark Coates:
Probabilistic Metric Learning with Adaptive Margin for Top-K Recommendation. CoRR abs/2101.04849 (2021) - [i36]Xinyi Dai, Jianghao Lin, Weinan Zhang, Shuai Li, Weiwen Liu, Ruiming Tang, Xiuqiang He, Jianye Hao, Jun Wang, Yong Yu:
An Adversarial Imitation Click Model for Information Retrieval. CoRR abs/2104.06077 (2021) - [i35]Huifeng Guo, Wei Guo, Yong Gao, Ruiming Tang, Xiuqiang He, Wenzhi Liu:
ScaleFreeCTR: MixCache-based Distributed Training System for CTR Models with Huge Embedding Table. CoRR abs/2104.08542 (2021) - [i34]Weinan Zhang, Jiarui Qin, Wei Guo, Ruiming Tang, Xiuqiang He:
Deep Learning for Click-Through Rate Estimation. CoRR abs/2104.10584 (2021) - [i33]Wei Guo, Rong Su, Renhao Tan, Huifeng Guo, Yingxue Zhang, Zhirong Liu, Ruiming Tang, Xiuqiang He:
Dual Graph enhanced Embedding Neural Network for CTR Prediction. CoRR abs/2106.00314 (2021) - [i32]Xiangli Yang, Qing Liu, Rong Su, Ruiming Tang, Zhirong Liu, Xiuqiang He:
AutoFT: Automatic Fine-Tune for Parameters Transfer Learning in Click-Through Rate Prediction. CoRR abs/2106.04873 (2021) - [i31]Weiwen Liu, Feng Liu, Ruiming Tang, Ben Liao, Guangyong Chen, Pheng-Ann Heng:
Balancing Accuracy and Fairness for Interactive Recommendation with Reinforcement Learning. CoRR abs/2106.13386 (2021) - [i30]Fuyuan Lyu, Xing Tang, Huifeng Guo, Ruiming Tang, Xiuqiang He, Rui Zhang, Xue Liu:
Memorize, Factorize, or be Naïve: Learning Optimal Feature Interaction Methods for CTR Prediction. CoRR abs/2108.01265 (2021) - [i29]Jiarui Qin, Weinan Zhang, Rong Su, Zhirong Liu, Weiwen Liu, Ruiming Tang, Xiuqiang He, Yong Yu:
Retrieval & Interaction Machine for Tabular Data Prediction. CoRR abs/2108.05252 (2021) - [i28]Yunzhe Li, Yue Ding, Bo Chen, Xin Xin, Yule Wang, Yuxiang Shi, Ruiming Tang, Dong Wang:
Extracting Attentive Social Temporal Excitation for Sequential Recommendation. CoRR abs/2109.13539 (2021) - [i27]Yunjia Xi, Weiwen Liu, Xinyi Dai, Ruiming Tang, Weinan Zhang, Qing Liu, Xiuqiang He, Yong Yu:
Context-aware Reranking with Utility Maximization for Recommendation. CoRR abs/2110.09059 (2021) - [i26]Yong Gao, Huifeng Guo, Dandan Lin, Yingxue Zhang, Ruiming Tang, Xiuqiang He:
Content Filtering Enriched GNN Framework for News Recommendation. CoRR abs/2110.12681 (2021) - [i25]Chenxu Zhu, Bo Chen, Weinan Zhang, Jincai Lai, Ruiming Tang, Xiuqiang He, Zhenguo Li, Yong Yu:
AIM: Automatic Interaction Machine for Click-Through Rate Prediction. CoRR abs/2111.03318 (2021) - [i24]Handong Ma, Jiawei Hou, Chenxu Zhu, Weinan Zhang, Ruiming Tang, Jincai Lai, Jieming Zhu, Xiuqiang He, Yong Yu:
QA4PRF: A Question Answering based Framework for Pseudo Relevance Feedback. CoRR abs/2111.08229 (2021) - [i23]Hang Lai, Jian Shen, Weinan Zhang, Yimin Huang, Xing Zhang, Ruiming Tang, Yong Yu, Zhenguo Li:
On Effective Scheduling of Model-based Reinforcement Learning. CoRR abs/2111.08550 (2021) - [i22]Wei Guo, Can Zhang, Zhicheng He, Jiarui Qin, Huifeng Guo, Bo Chen, Ruiming Tang, Xiuqiang He, Rui Zhang:
MISS: Multi-Interest Self-Supervised Learning Framework for Click-Through Rate Prediction. CoRR abs/2111.15068 (2021) - [i21]Yankai Chen, Yifei Zhang, Yingxue Zhang, Huifeng Guo, Jingjie Li, Ruiming Tang, Xiuqiang He, Irwin King:
Towards Low-loss 1-bit Quantization of User-item Representations for Top-K Recommendation. CoRR abs/2112.01944 (2021) - 2020
- [j5]Feng Liu, Ruiming Tang, Huifeng Guo, Xutao Li, Yunming Ye, Xiuqiang He:
Top-aware reinforcement learning based recommendation. Neurocomputing 417: 255-269 (2020) - [j4]Feng Liu, Ruiming Tang, Xutao Li, Weinan Zhang, Yunming Ye, Haokun Chen, Huifeng Guo, Yuzhou Zhang, Xiuqiang He:
State representation modeling for deep reinforcement learning based recommendation. Knowl. Based Syst. 205: 106170 (2020) - [c44]Bo Chen, Wei Guo, Ruiming Tang, Xin Xin, Yue Ding, Xiuqiang He, Dong Wang:
TGCN: Tag Graph Convolutional Network for Tag-Aware Recommendation. CIKM 2020: 155-164 - [c43]Farhan Khawar, Xu Hang, Ruiming Tang, Bin Liu, Zhenguo Li, Xiuqiang He:
AutoFeature: Searching for Feature Interactions and Their Architectures for Click-through Rate Prediction. CIKM 2020: 625-634 - [c42]Weiwen Liu, Qing Liu, Ruiming Tang, Junyang Chen, Xiuqiang He, Pheng-Ann Heng:
Personalized Re-ranking with Item Relationships for E-commerce. CIKM 2020: 925-934 - [c41]Xinyi Dai, Jiawei Hou, Qing Liu, Yunjia Xi, Ruiming Tang, Weinan Zhang, Xiuqiang He, Jun Wang, Yong Yu:
U-rank: Utility-oriented Learning to Rank with Implicit Feedback. CIKM 2020: 2373-2380 - [c40]Yishi Xu, Yingxue Zhang, Wei Guo, Huifeng Guo, Ruiming Tang, Mark Coates:
GraphSAIL: Graph Structure Aware Incremental Learning for Recommender Systems. CIKM 2020: 2861-2868 - [c39]Weijun Hong, Guilin Li, Weinan Zhang, Ruiming Tang, Yunhe Wang, Zhenguo Li, Yong Yu:
DropNAS: Grouped Operation Dropout for Differentiable Architecture Search. IJCAI 2020: 2326-2332 - [c38]